Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 25, issue 6
Articles | Volume 25, issue 6
https://doi.org/10.5194/nhess-25-1841-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-1841-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 6
Research article
 | 
03 Jun 2025
Research article |  | 03 Jun 2025

Exploring implications of input parameter uncertainties in glacial lake outburst flood (GLOF) modelling results using the modelling code r.avaflow

Sonam Rinzin, Stuart Dunning, Rachel Joanne Carr, Ashim Sattar, and Martin Mergili

Viewed

Total article views: 2,611 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,767 691 153 2,611 183 89 117
  • HTML: 1,767
  • PDF: 691
  • XML: 153
  • Total: 2,611
  • Supplement: 183
  • BibTeX: 89
  • EndNote: 117
Views and downloads (calculated since 17 Jul 2024)
Cumulative views and downloads (calculated since 17 Jul 2024)

Viewed (geographical distribution)

Total article views: 2,611 (including HTML, PDF, and XML) Thereof 2,493 with geography defined and 118 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 30 Apr 2026
Download
Short summary
We modelled multiple glacial lake outburst flood (GLOF) scenarios (84 simulations) and tested the effect of nine key input parameters on the modelling results using r.avaflow. Our results highlight that GLOF modelling results are subject to uncertainty from the multiple input parameters. The variation in the volume of mass movement entering the lake causes the highest uncertainty in the modelled GLOF, followed by the DEM dataset and the origin of mass movement.
Read more
Share
Altmetrics
Final-revised paper
Preprint